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Analysis of Genetic Alterations in Tunisian Patients with Lung Adenocarcinoma.

Dhoha Dhieb | Imen Belguith | Laura Capelli | Elisa Chiadini | Matteo Canale | Sara Bravaccini | Ilhem Yangui | Ons Boudawara | Rachid Jlidi | Tahya Boudawara | Daniele Calistri | Leila Ammar Keskes | Paola Ulivi
Cells | 2019

The identification of the mutations that drive lung cancer have furnished new targets for the treatment of non-small cell lung cancer (NSCLC) and led to the development of targeted therapies such as tyrosine kinase inhibitors that are used to combat the molecular changes promoting cancer progression. Furthermore, biomarkers identified from gene analysis can be used to detect early lung cancer, determine patient prognosis, and monitor response to therapy. In the present study we analyzed the molecular profile of seventy-three Tunisian patients with lung adenocarcinoma (LAD). Mutational analyses for EGFR and KRAS were performed using direct sequencing, immunohistochemistry or MassARRAY. Anaplastic lymphoma kinase (ALK) rearrangement was evaluated by immunohistochemistry using the D5F3 clone, and p53 expression was also assessed. The median age of patients at diagnosis was 61 years (range 23-82 years). Using different methodologies, EGFR mutations were found in 5.47% of patients and only exon 19 deletions "E746-A750 del" were detected. KRAS mutations were present in 9.58% of cases, while only one patient was ALK-positive. Moreover, abnormal immunostaining of p53 was detected in 56.16% of patients. In conclusion, the detected rates of EGFR and KRAS mutation and ALK rearrangement were lower than those found in European and Asian countries, whereas, abnormal p53 expression was slightly more frequent. Furthermore, given the small sample size of this study, a more comprehensive analysis of this patient set is warranted.

Pubmed ID: 31141932

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QIAGEN (tool)

RRID:SCR_008539

A commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.

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Motif Mutation Analysis for Regulatory Genomic Elements (tool)

RRID:SCR_021902

Software package that integrates genome wide genetic variation with epigenetic data to identify collaborative transcription factor pairs. Optimized to work with chromatin accessibility assays such as ATAC-seq or DNase I hypersensitivity, as well as transcription factor binding data collected by ChIP-seq. Used to identify combinations of cell type specific transcription factors while simultaneously interpreting functional effects of non-coding genetic variation.

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